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Allow OpenAI API URL to be configured via assistant.openai_api_url
(#7552)
Partially fixes #4321, since Azure OpenAI API can be converted to OpenAI API. Release Notes: - Added `assistant.openai_api_url` setting to allow OpenAI API URL to be configured. --------- Co-authored-by: Marshall Bowers <elliott.codes@gmail.com>
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@ -212,6 +212,8 @@
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"default_width": 640,
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// Default height when the assistant is docked to the bottom.
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"default_height": 320,
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// The default OpenAI API endpoint to use when starting new conversations.
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"openai_api_url": "https://api.openai.com/v1",
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// The default OpenAI model to use when starting new conversations. This
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// setting can take three values:
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//
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@ -103,6 +103,7 @@ pub struct OpenAiResponseStreamEvent {
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}
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pub async fn stream_completion(
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api_url: String,
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credential: ProviderCredential,
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executor: BackgroundExecutor,
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request: Box<dyn CompletionRequest>,
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@ -117,7 +118,7 @@ pub async fn stream_completion(
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let (tx, rx) = futures::channel::mpsc::unbounded::<Result<OpenAiResponseStreamEvent>>();
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let json_data = request.data()?;
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let mut response = Request::post(format!("{OPEN_AI_API_URL}/chat/completions"))
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let mut response = Request::post(format!("{api_url}/chat/completions"))
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.header("Content-Type", "application/json")
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.header("Authorization", format!("Bearer {}", api_key))
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.body(json_data)?
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@ -195,18 +196,20 @@ pub async fn stream_completion(
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#[derive(Clone)]
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pub struct OpenAiCompletionProvider {
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api_url: String,
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model: OpenAiLanguageModel,
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credential: Arc<RwLock<ProviderCredential>>,
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executor: BackgroundExecutor,
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}
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impl OpenAiCompletionProvider {
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pub async fn new(model_name: String, executor: BackgroundExecutor) -> Self {
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pub async fn new(api_url: String, model_name: String, executor: BackgroundExecutor) -> Self {
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let model = executor
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.spawn(async move { OpenAiLanguageModel::load(&model_name) })
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.await;
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let credential = Arc::new(RwLock::new(ProviderCredential::NoCredentials));
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Self {
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api_url,
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model,
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credential,
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executor,
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@ -303,7 +306,8 @@ impl CompletionProvider for OpenAiCompletionProvider {
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// which is currently model based, due to the language model.
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// At some point in the future we should rectify this.
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let credential = self.credential.read().clone();
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let request = stream_completion(credential, self.executor.clone(), prompt);
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let api_url = self.api_url.clone();
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let request = stream_completion(api_url, credential, self.executor.clone(), prompt);
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async move {
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let response = request.await?;
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let stream = response
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@ -35,6 +35,7 @@ lazy_static! {
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#[derive(Clone)]
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pub struct OpenAiEmbeddingProvider {
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api_url: String,
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model: OpenAiLanguageModel,
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credential: Arc<RwLock<ProviderCredential>>,
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pub client: Arc<dyn HttpClient>,
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@ -69,7 +70,11 @@ struct OpenAiEmbeddingUsage {
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}
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impl OpenAiEmbeddingProvider {
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pub async fn new(client: Arc<dyn HttpClient>, executor: BackgroundExecutor) -> Self {
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pub async fn new(
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api_url: String,
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client: Arc<dyn HttpClient>,
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executor: BackgroundExecutor,
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) -> Self {
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let (rate_limit_count_tx, rate_limit_count_rx) = watch::channel_with(None);
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let rate_limit_count_tx = Arc::new(Mutex::new(rate_limit_count_tx));
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@ -80,6 +85,7 @@ impl OpenAiEmbeddingProvider {
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let credential = Arc::new(RwLock::new(ProviderCredential::NoCredentials));
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OpenAiEmbeddingProvider {
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api_url,
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model,
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credential,
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client,
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@ -130,11 +136,12 @@ impl OpenAiEmbeddingProvider {
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}
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async fn send_request(
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&self,
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api_url: &str,
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api_key: &str,
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spans: Vec<&str>,
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request_timeout: u64,
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) -> Result<Response<AsyncBody>> {
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let request = Request::post(format!("{OPEN_AI_API_URL}/embeddings"))
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let request = Request::post(format!("{api_url}/embeddings"))
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.redirect_policy(isahc::config::RedirectPolicy::Follow)
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.timeout(Duration::from_secs(request_timeout))
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.header("Content-Type", "application/json")
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@ -246,6 +253,7 @@ impl EmbeddingProvider for OpenAiEmbeddingProvider {
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const BACKOFF_SECONDS: [usize; 4] = [3, 5, 15, 45];
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const MAX_RETRIES: usize = 4;
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let api_url = self.api_url.as_str();
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let api_key = self.get_api_key()?;
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let mut request_number = 0;
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@ -255,6 +263,7 @@ impl EmbeddingProvider for OpenAiEmbeddingProvider {
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while request_number < MAX_RETRIES {
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response = self
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.send_request(
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&api_url,
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&api_key,
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spans.iter().map(|x| &**x).collect(),
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request_timeout,
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@ -68,6 +68,7 @@ struct SavedConversation {
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messages: Vec<SavedMessage>,
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message_metadata: HashMap<MessageId, MessageMetadata>,
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summary: String,
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api_url: Option<String>,
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model: OpenAiModel,
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}
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@ -7,6 +7,7 @@ use crate::{
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SavedMessage, Split, ToggleFocus, ToggleIncludeConversation, ToggleRetrieveContext,
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};
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use ai::prompts::repository_context::PromptCodeSnippet;
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use ai::providers::open_ai::OPEN_AI_API_URL;
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use ai::{
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auth::ProviderCredential,
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completion::{CompletionProvider, CompletionRequest},
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@ -121,10 +122,22 @@ impl AssistantPanel {
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.await
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.log_err()
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.unwrap_or_default();
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// Defaulting currently to GPT4, allow for this to be set via config.
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let completion_provider =
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OpenAiCompletionProvider::new("gpt-4".into(), cx.background_executor().clone())
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.await;
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let (api_url, model_name) = cx
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.update(|cx| {
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let settings = AssistantSettings::get_global(cx);
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(
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settings.openai_api_url.clone(),
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settings.default_open_ai_model.full_name().to_string(),
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)
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})
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.log_err()
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.unwrap();
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let completion_provider = OpenAiCompletionProvider::new(
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api_url,
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model_name,
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cx.background_executor().clone(),
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)
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.await;
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// TODO: deserialize state.
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let workspace_handle = workspace.clone();
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@ -1407,6 +1420,7 @@ struct Conversation {
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completion_count: usize,
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pending_completions: Vec<PendingCompletion>,
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model: OpenAiModel,
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api_url: Option<String>,
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token_count: Option<usize>,
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max_token_count: usize,
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pending_token_count: Task<Option<()>>,
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@ -1441,6 +1455,7 @@ impl Conversation {
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let settings = AssistantSettings::get_global(cx);
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let model = settings.default_open_ai_model.clone();
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let api_url = settings.openai_api_url.clone();
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let mut this = Self {
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id: Some(Uuid::new_v4().to_string()),
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@ -1454,6 +1469,7 @@ impl Conversation {
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token_count: None,
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max_token_count: tiktoken_rs::model::get_context_size(&model.full_name()),
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pending_token_count: Task::ready(None),
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api_url: Some(api_url),
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model: model.clone(),
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_subscriptions: vec![cx.subscribe(&buffer, Self::handle_buffer_event)],
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pending_save: Task::ready(Ok(())),
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@ -1499,6 +1515,7 @@ impl Conversation {
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.map(|summary| summary.text.clone())
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.unwrap_or_default(),
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model: self.model.clone(),
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api_url: self.api_url.clone(),
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}
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}
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@ -1513,8 +1530,12 @@ impl Conversation {
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None => Some(Uuid::new_v4().to_string()),
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};
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let model = saved_conversation.model;
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let api_url = saved_conversation.api_url;
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let completion_provider: Arc<dyn CompletionProvider> = Arc::new(
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OpenAiCompletionProvider::new(
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api_url
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.clone()
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.unwrap_or_else(|| OPEN_AI_API_URL.to_string()),
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model.full_name().into(),
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cx.background_executor().clone(),
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)
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@ -1567,6 +1588,7 @@ impl Conversation {
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token_count: None,
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max_token_count: tiktoken_rs::model::get_context_size(&model.full_name()),
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pending_token_count: Task::ready(None),
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api_url,
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model,
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_subscriptions: vec![cx.subscribe(&buffer, Self::handle_buffer_event)],
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pending_save: Task::ready(Ok(())),
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@ -55,6 +55,7 @@ pub struct AssistantSettings {
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pub default_width: Pixels,
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pub default_height: Pixels,
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pub default_open_ai_model: OpenAiModel,
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pub openai_api_url: String,
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}
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/// Assistant panel settings
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@ -80,6 +81,10 @@ pub struct AssistantSettingsContent {
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///
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/// Default: gpt-4-1106-preview
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pub default_open_ai_model: Option<OpenAiModel>,
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/// OpenAI API base URL to use when starting new conversations.
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///
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/// Default: https://api.openai.com/v1
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pub openai_api_url: Option<String>,
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}
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impl Settings for AssistantSettings {
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@ -8,7 +8,7 @@ mod semantic_index_tests;
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use crate::semantic_index_settings::SemanticIndexSettings;
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use ai::embedding::{Embedding, EmbeddingProvider};
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use ai::providers::open_ai::OpenAiEmbeddingProvider;
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use ai::providers::open_ai::{OpenAiEmbeddingProvider, OPEN_AI_API_URL};
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use anyhow::{anyhow, Context as _, Result};
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use collections::{BTreeMap, HashMap, HashSet};
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use db::VectorDatabase;
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@ -91,8 +91,13 @@ pub fn init(
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.detach();
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cx.spawn(move |cx| async move {
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let embedding_provider =
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OpenAiEmbeddingProvider::new(http_client, cx.background_executor().clone()).await;
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let embedding_provider = OpenAiEmbeddingProvider::new(
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// TODO: We should read it from config, but I'm not sure whether to reuse `openai_api_url` in assistant settings or not
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OPEN_AI_API_URL.to_string(),
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http_client,
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cx.background_executor().clone(),
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)
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.await;
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let semantic_index = SemanticIndex::new(
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fs,
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db_file_path,
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